Coercing users to disclose their credentials (a.k.a.
rubber-hose attacks) has been the bane of classic cryptography. We
discuss our ongoing work on designing coercion-resistant security
primitives based on implicit learning. We present our current results
as well as experimental setup using Amazon's Mechanical Turk service.
We also map out directions for future work that we plan to pursue.

Bio:

Hristo Bojinov is a PhD candidate at Stanford's Security Lab. His work on mobile and web security is advised by Prof. Dan Boneh. Prior to Stanford, Hristo spent a number of years in industry, building enterprise software and storage security products. Hristo has a M.S. from Stanford University, and S.B. from MIT.